Mohammad S. E. Sendi is currently an NIMH T32 postdoctoral fellow at Mclean Hospital and Harvard Medical School. At the interface between neuroscience and machine learning, his research focuses on applying machine learning techniques to elucidate the underlying mechanism of neuropsychiatric disorders and develop new treatments. He is interested in finding new multimodal biomarkers for depression and PTSD. Previously, he developed multiple frameworks to analyze dynamic functional network connectivity estimated from resting-state fMRI and identified new biomarkers in depression, schizophrenia, and Alzheimer’s disease. He also developed an active learning framework to optimally sample the brain stimulation parameters for closed-loop neuromodulation. His long-term goal is to create personalized therapy based on patient genotype and brain phenotype information in neuropsychiatric disorders.